The Dynamics of Vehicular Networks in Urban Environments

Vehicular Ad hoc NETworks (VANETs) have emerged as a platform to support intelligent inter-vehicle communication and improve traffic safety and performance. The road-constrained, high mobility of vehicles, their unbounded power source, and the emergence of roadside wireless infrastructures make VANETs a challenging research topic. A key to the development of protocols for inter-vehicle communication and services lies in the knowledge of the topological characteristics of the VANET communication graph. This paper explores the dynamics of VANETs in urban environments and investigates the impact of these findings in the design of VANET routing protocols. Using both real and realistic mobility traces, we study the networking shape of VANETs under different transmission and market penetration ranges. Given that a number of RSUs have to be deployed for disseminating information to vehicles in an urban area, we also study their impact on vehicular connectivity. Through extensive simulations we investigate the performance of VANET routing protocols by exploiting the knowledge of VANET graphs analysis.Comment: Revised our testbed with even more realistic mobility traces. Used the location of real Wi-Fi hotspots to simulate RSUs in our study. Used a larger, real mobility trace set, from taxis in Shanghai. Examine the implications of our findings in the design of VANET routing protocols by implementing in ns-3 two routing protocols (GPCR & VADD). Updated the bibliography section with new research work

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Previous hop routing: exploiting opportunism in VANETs

Routing in highly dynamic wireless networks such as Vehicular Ad-hoc Networks (VANETs) is a challenging task due to frequent topology changes. Sustaining a transmission path between peers in such network environment is difficult. In this thesis, Previous Hop Routing (PHR) is poposed; an opportunistic forwarding protocol exploiting previous hop information and distance to destination to make the forwarding decision on a packet-by-packet basis. It is intended for use in highly dynamic network where the life time of a hop-by-hop path between source and destination nodes is short. Exploiting the broadcast nature of wireless communication avoids the need to copy packets, and enables redundant paths to be formed. To save network resources, especially under high network loads, PHR employs probabilistic forwarding. The forwarding probability is calculated based on the perceived network load as measured by the arrival rate at the network interface. We evaluate PHR in an urban VANET environment using NS2 (for network traffic) and SUMO (for vehicular movement) simulators, with scenarios configured to re ect real-world conditions. The simulation scenarios are configured to use two velocity profiles i.e. Low and high velocity. The results show that the PHR networks able to achieve best performance as measured by Packet Delivery Ratio (PDR) and Drop Burst Length (DBL) compared to conventional routing protocols in high velocity scenarios

Vehicular Networks with Infrastructure: Modeling, Simulation and Testbed

This thesis focuses on Vehicular Networks with Infrastructure. In the examined scenarios, vehicular nodes (e.g., cars, buses) can communicate with infrastructure roadside units (RSUs) providing continuous or intermittent coverage of an urban road topology. Different aspects related to the design of new applications for Vehicular Networks are investigated through modeling, simulation and testing on real field. In particular, the thesis: i) provides a feasible multi-hop routing solution for maintaining connectivity among RSUs, forming the wireless mesh infrastructure, and moving vehicles; ii) explains how to combine the UHF and the traditional 5-GHz bands to design and implement a new high-capacity high-efficiency Content Downloading using disjoint control and service channels; iii) studies new RSUs deployment strategies for Content Dissemination and Downloading in urban and suburban scenarios with different vehicles mobility models and traffic densities; iv) defines an optimization problem to minimize the average travel delay perceived by the drivers, spreading different traffic flows over the surface roads in a urban scenario; v) exploits the concept of Nash equilibrium in the game-theory approach to efficiently guide electric vehicles drivers' towards the charging stations. Moreover, the thesis emphasizes the importance of using realistic mobility models, as well as reasonable signal propagation models for vehicular networks. Simplistic assumptions drive to trivial mathematical analysis and shorter simulations, but they frequently produce misleading results. Thus, testing the proposed solutions in the real field and collecting measurements is a good way to double-check the correctness of our studie

Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems

Intelligent transportation systems (ITSs) have been fueled by the rapid development of communication technologies, sensor technologies, and the Internet of Things (IoT). Nonetheless, due to the dynamic characteristics of the vehicle networks, it is rather challenging to make timely and accurate decisions of vehicle behaviors. Moreover, in the presence of mobile wireless communications, the privacy and security of vehicle information are at constant risk. In this context, a new paradigm is urgently needed for various applications in dynamic vehicle environments. As a distributed machine learning technology, federated learning (FL) has received extensive attention due to its outstanding privacy protection properties and easy scalability. We conduct a comprehensive survey of the latest developments in FL for ITS. Specifically, we initially research the prevalent challenges in ITS and elucidate the motivations for applying FL from various perspectives. Subsequently, we review existing deployments of FL in ITS across various scenarios, and discuss specific potential issues in object recognition, traffic management, and service providing scenarios. Furthermore, we conduct a further analysis of the new challenges introduced by FL deployment and the inherent limitations that FL alone cannot fully address, including uneven data distribution, limited storage and computing power, and potential privacy and security concerns. We then examine the existing collaborative technologies that can help mitigate these challenges. Lastly, we discuss the open challenges that remain to be addressed in applying FL in ITS and propose several future research directions